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Amrita-CEN@MSIR-FIRE2016: Code-mixed question classification using BoWs and RNN Embeddings

Publication Type : Conference Paper

Publisher : CEUR Workshop Proceedings, CEUR-WS.

Source : CEUR Workshop Proceedings, CEUR-WS, Volume 1737, p.122-125 (2016)

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Keywords : Artificial intelligence, Code-mixed script, Codes (symbols), Embeddings, Extracting features, Information Retrieval, Knowledge based systems, Knowledge-based methods, Learning systems, Logistic regressions, Question Answering, Question classification, Recurrent neural networks, Sentence level, Text processing

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Electronics and Communication

Year : 2016

Abstract : Question classification is a key task in many question answering applications. Nearly all previous work on question classification has used machine learning and knowledge-based methods. This working note presents an embedding based Bag-of-Words method and Recurrent Neural Network to achieve an automatic question classification in the code-mixed Bengali-English text. We build two systems that classify questions mostly at the sentence level. We used a recurrent neural network for extracting features from the questions and Logistic regression for classification. We conduct experiments on Mixed Script Information Retrieval (MSIR) Task 1 dataset at FIRE20161. The experimental result shows that the proposed method is appropriate for the question classification task.

Cite this Research Publication : Dr. M. Anand Kumar, Dr. Soman K. P., and Dr. Soman K. P., “Amrita-CEN@MSIR-FIRE2016: Code-mixed question classification using BoWs and RNN Embeddings”, in CEUR Workshop Proceedings, 2016, vol. 1737, pp. 122-125.

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